Influence of cooking method, fat content and food additives on physicochemical and nutritional properties of beef meatballs fortified with sugarcane fibre
Bibliographic record
Abstract
Summary This study explored effects of different cooking methods, pork fat addition and food additives on physicochemical and nutritional attributes of beef meatballs fortified, or not, with 3% sugarcane fibre. TPA hardness of meatballs with fibre, cooked in boiling water, was lower compared to oven‐baked and pan‐fried (47.11, 56.24 and 59.22 N, respectively). Hardness also decreased with increasing fat content (5%, 10%, 15% and 20% fat; 62.07, 56.96, 54.02 and 45.51 N, respectively). Tetrasodium pyrophosphate and sodium tripolyphosphate provided similar results for all parameters except ash content where cooked meatballs with the latter were higher (1.98% and 2.22%, respectively). Cooking loss of 20% fat meatballs with fibre was lower (17.14%) compared to without fibre (20.28%). Loss of nutrients after cooking was lower for oven‐baked compared to boiling. Using different ingredients to manipulate quality traits of meatballs is an alternative to manufacture suitable products for different market requirements, for example for elderly consumers.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".